Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Yuriy Nevmyvaka"'
Autor:
Sanjay Purushotham, Jun Huan, Cong Shen, Dongjin Song, Yuyang Wang, Jan Gasthaus, Hilaf Hasson, Youngsuk Park, Sungyong Seo, Yuriy Nevmyvaka
Publikováno v:
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b1de14f72765e07654e487dfa081e979
https://doi.org/10.1145/3534678.3542889
https://doi.org/10.1145/3534678.3542889
Publikováno v:
The Journal of Trading. 5:50-62
Addressing the ongoing controversy of overly aggressive high-frequency trading practices in financial markets, Kearns, Kulesza, and Nevmyvaka report the results of an extensive empirical study estimating the maximum possible profitability of such pra
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ef72345127adb5248f56d7838d6006c7
https://doi.org/10.3905/jot.2010.5.4.050
https://doi.org/10.3905/jot.2010.5.4.050
We introduce and analyze a natural algorithm for multi-venue exploration from censored data, which is motivated by the Dark Pool Problem of modern quantitative finance. We prove that our algorithm converges in polynomial time to a near-optimal alloca
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c689ac0743cb45c9ce4597bc7cd0a47b
http://arxiv.org/abs/1205.2646
http://arxiv.org/abs/1205.2646
Publikováno v:
SSRN Electronic Journal.
Addressing the ongoing examination of high-frequency trading practices in financial markets, we report the results of an extensive empirical study estimating the maximum possible profitability of the most aggressive such practices, and arrive at figu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0045ff8aca91e152a3d5bc01ce62360e
https://doi.org/10.2139/ssrn.1678758
https://doi.org/10.2139/ssrn.1678758
Publikováno v:
ICML
We present the first large-scale empirical application of reinforcement learning to the important problem of optimized trade execution in modern financial markets. Our experiments are based on 1.5 years of millisecond time-scale limit order data from
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2063b031a936ae336a28f7c6db45776a
https://doi.org/10.1145/1143844.1143929
https://doi.org/10.1145/1143844.1143929